Using Semantic Technology to Identify Nature

Identifying any part of nature is not easy. The discipline of classification and taxonomy involves the grouping of organisms into categories based on different properties including size, shape and gene sequences. Classification can help to identify evolutionary relationships among organisms, but it takes time; a lot of time. This interesting information came from Wired in their article, “A Computer With a Great Eye Is About to Transform Botany.”

Just correctly identifying a single leaf’s taxonomy can take two hours, says Peter Wilf, paleobotanist at Penn State’s College of Earth and Mineral Sciences. For the past nine years, Wilf has worked with a computational neuroscientist from Brown University to program computer software to do what the human eye cannot: identify families of leaves, in mere milliseconds.

The software combines computer vision and machine learning algorithms to identify patterns in leaves, linking them to families of leaves they potentially evolved from with 72 percent accuracy. It is a taxonomy based on machine learning and image recognition.

“Everyone”—at least, every paleobotanist—“has had that dream in their head, if only I could just take a picture of this, and get an identity,” says Ellen Currano, an assistant professor in the Department of Geology and Geophysics at the University of Wyoming.

Melody K. Smith

Sponsored by Access Innovations, the world leader in thesaurus, ontology, and taxonomy creation and metadata application.